Despite the term ‘survival’ in survival analysis, it is not only used for analysis of survival data but it can be used for a wide area of applications. Read to find out more!

Photo by Andreas Wagner on Unsplash

What is Survival Analysis?

Survival analysis is a branch of statistics that is used to analyze the expected time until an event of interest occurs. The response is often referred to as event time or survival time. It is used to know how long until an event, for example, death occurs. However, survival analysis is not only restricted to analyzing survival times but can be used for answering various questions such…

Tutorial on implementing Embeddings learned by a neural net in ML models

Photo by Mika Baumeister on Unsplash

This article’s purpose is to provide information on how to implement Embeddings learned by a neural net in ML models. Thus, we won’t go into detail about the theory of Embeddings.

Note: It is assumed that you know the basics of Deep Learning and Machine Learning

What are Entity Embeddings and why use Entity Embeddings?

To put it loosely, an entity embedding is a vector representation of categorical variables in a continuous manner. In the context of neural networks, embeddings transform features from its original space into a low-dimensional vector space representation for each instance while preserving the information from its features and also meaningfully represent each category in…

How we can use regression models, random forests and neural networks to predict a student’s chance of gaining admission into Graduate School?


The objective of this analysis is to explore the most important factors for a student to get into graduate school and to select the most accurate model to predict a student’s chances of gaining admission into Graduate School.

The data that I will be using is the Graduates Admission 2 dataset that can be found on Kaggle which is inspired by the UCLA Admissions dataset.

Importing required libraries

#import required libraries
from pandas.api.types import is_string_dtype, is_numeric_dtype, is_categorical_dtype
from fastai.tabular.all import *
from sklearn.ensemble import RandomForestRegressor
from sklearn.tree import DecisionTreeRegressor
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from IPython.display import Image, display_svg, SVG
import pandas as pd
import seaborn…

Like every NBA fan, I spend most of my day watching NBA games. One day, while watching one of the best passers in the NBA, Nikola Jokić, dropping yet another fancy no-look pass while leading the Nuggets to another victory, a question popped into my head, ‘Who is the best passer in the NBA currently? Is it Jokić, the MVP frontrunner? Is it Point God, Chris Paul? Or is it Russell Westbrook who is leading the league in assists this season?’

To find out, let’s carry out some analysis via simple data visualizations. In this particular ranking, we will be…

Jia Qing

Aspiring data scientist, sports fan, tech enthusiast.

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